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Overview of current practices in data analysis for wood identification. A guide for the different timber tracking methods.
Abstract and Figures
Today we have five types of timber tracking tools available. Each has its own strengths and limitations (see the Timber Tracking Tool Infogram), but together they offer a broad range of methods that can assist us in identifying the botanical as well as the geographic origin (provenance) of most kinds of timber samples, even those smaller than 1 cm³.
With this guide we want to provide an overview of the current best-practice methods used to analyse data derived from different wood identification methods, while presenting their respective strengths and limitations. We give advice on data analysis, from the development of reference data, through to the verification of identity and provenance of unknown samples against the reference database. We end with an expert view on combining methods for wood identification and discuss how timber identification possibilities could expand in the future.
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... NIRS measures a material's reflectance, transmittance, or absorbance spectra when exposed to near-infrared electromagnetic energy under specific conditions (UNODC 2016;Beeckman et al. 2020). This process allows the profiling of a specific taxon from a particular geographical area (Beeckman et al. 2020). ...
... NIRS measures a material's reflectance, transmittance, or absorbance spectra when exposed to near-infrared electromagnetic energy under specific conditions (UNODC 2016;Beeckman et al. 2020). This process allows the profiling of a specific taxon from a particular geographical area (Beeckman et al. 2020). ...
... Standard samples and mathematical standardisation procedures may be necessary when different machines are used, requiring the transfer of a statistical model (model transfer) (Wang et al. 1991;Honorato et al. 2007). This accounts for differences in calibration settings even when labs are equipped with the same type of equipment (bench or portable) from the same manufacturer or model (Beeckman et al. 2020). It is also important to note that the raw spectroscopic outputs are typically not directly informative and must be subjected to appropriate multivariate analyses to yield meaningful results (Pastore et al. 2011;UNODC 2016). ...
Wood identification, whether it involves distinguishing between known species or identifying unfamiliar wood samples, is a scientific field increasingly valuable across various disciplines ranging from biology to criminology, structural engineering, and art conservation. It carries a growing economic, commercial, social, and ecological significance. Numerous scientific methods have been employed for wood identification. Visual analysis techniques, such as macroscopy, optical microscopy, scanning electron microscopy, X-ray tomography, and computer-assisted wood identification, play a pivotal role. Analytical approaches like mass spectrometry, near-infrared spectroscopy, thermogravimetry, and DNA barcoding have also been utilised. However, chromatography stands out due to its exceptional precision in providing quantitative and qualitative results, prompting its development and widespread use. This paper offers a critical review of the role of chromatography in wood identification. Advantages are highlighted, including the capability to identify specific components unique to each wood species, thus achieving remarkable differentiation at the species level. Additionally, potential drawbacks are discussed, such as the time-intensive sample preparation procedures, mainly when dealing with materials like wood-polymer composites (WPC), and the absence of an open-source database. This comprehensive analysis aims to provide a broader perspective on the possibilities and limitations of this technique.
... To ensure Table 1. Protocol for the construction of a xylarium (Bridson and Forman 2010;British Columbia Ministry of Forests 1996;Esteban et al. 2012;Perkins 2022;RHS -Royal Horticultural Society 2013;Schmitz et al. 2019Schmitz et al. , 2020Wiedenhoeft 2014). ...
... Especially for xylarium, the drying time depends, among other factors, on the thickness of the sample, the species density, the season of collection and the drying conditions. For a Table 4. Protocol for xylarium and herbarium field description and specimen labelling (Bridson and Forman 2010;British Columbia Ministry of Forests 1996;Perkins 2022;RHS -Royal Horticultural Society 2013;Schmitz et al. 2019Schmitz et al. , 2020. ...
The significance of plant material sample deposits extends beyond the scientific community, with various industries, historians, and law enforcement agencies increasingly relying on them. Preserving global xylariums and herbariums is essential for accessing centuries of data, species, and samples that may no longer exist in their original locations or may be extinct. While maintaining these archives is crucial, it is equally important to ensure proper collection, structure, organization, and classification of new xylariums and herbariums. In that order, a preventive conservation approach is essential to ensure future research by defining actions, materials, and uses to prevent degradative factors and potential harm to the collection This guarantees future accessibility to valuable samples and the knowledge they offer. The paper explores key factors in xylarium and herbarium construction and preservation, including sample drying, pest control, preventive measures, archival materials, facilities, and handling procedures. ARTICLE HISTORY
... To date, the lack of accessible reference samples of relevant species and analytical methodologies designed for the verification of manufacturer-supplied data has been constantly shrinking. Forensic identification techniques for wood, can broadly be categorized as anatomical, chemical, and genetic methodologies Low et al. 2022;Lowe and Cross 2011;Schmitz et al. 2020). Solid wood is generally easier to identify using different methods with similarly good results (Ravindran and Wiedenhoeft 2020). ...
... Wood-based products such as pulp, paper and particle board tend to be more difficult to identify than solid wood (Sieburg-Rockel and Koch 2020). The selection of the most appropriate technique depends on the specific identification inquiry in question Schmitz et al. 2019Schmitz et al. , 2020. Notably, for the genus-level identification of pulp and paper products, exclusively anatomical and chemotaxonomic approaches prove applicable. ...
This paper presents a comparative analysis of the blind test outcomes of two independent methods for the identification of tropical wood species in pulp and paper products. Both, the established anatomical and the relatively new chemotaxonomic method support the European Deforestation Regulation 2023/1115 (EUDR), which aims to ensure that only legally harvested timber that has not contributed to deforestation is traded in the EU. The blind test involved 570 decisions on 15 test sheets of 37 self-manufactured mixed tropical hardwood pulps and an industrial beech pulp, used as a matrix. Both detection techniques demonstrated robust performance with over 80 % hit rates. The results show that the synergies and combination of the strengths of both methods can be utilized and lead to even better combined performance. In order to establish the chemotaxonomic identification method as a complement to the conventional anatomy-based method, statistical analyses were performed to assess its intermediate precision between three different GC-MS systems. In most cases, the method gave consistent results independent of the instrument used.
... Wood anatomy is one of the most important methods for field wood identification [10,14,15], and is performed by observing various anatomical features using a hand lens in three orthogonal directions, i.e., cross, radial, and tangential [16]. However, wood identification is a difficult task that requires specialized anatomical knowledge and a wide range of interspecies and intraspecies similarities [17]. ...
... However, current studies have only focused on improving accuracy and has not been able to explain the specific features used for classification [34]. This study demonstrates that the combination of deep learning with microscopic images yields better performance [14,35] and further provides the explanation deep-learning classification results by feature visualization. ...
Background
Traditional method of wood species identification involves the use of hand lens by wood anatomists, which is a time-consuming method that usually identifies only at the genetic level. Computer vision method can achieve "species" level identification but cannot provide an explanation on what features are used for the identification. Thus, in this study, we used computer vision methods coupled with deep learning to reveal interspecific differences between closely related tree species.
Result
A total of 850 images were collected from the cross and tangential sections of 15 wood species. These images were used to construct a deep-learning model to discriminate wood species, and a classification accuracy of 99.3% was obtained. The key features between species in machine identification were targeted by feature visualization methods, mainly the axial parenchyma arrangements and vessel in cross section and the wood ray in tangential section. Moreover, the degree of importance of the vessels of different tree species in the cross-section images was determined by the manual feature labeling method. The results showed that vessels play an important role in the identification of Dalbergia, Pterocarpus, Swartzia, Carapa, and Cedrela, but exhibited limited resolutions on discriminating Swietenia species.
Conclusion
The research results provide a computer-assisted tool for identifying endangered tree species in laboratory scenarios, which can be used to combat illegal logging and related trade and contribute to the implementation of CITES convention and the conservation of global biodiversity.
... Therefore, neither genetics, stable isotopes nor NIR spectroscopy can be used. It is therefore not possible to analyze the origin [2,3]. Recently a new, very complex chemotaxonomic method for determining wood species was introduced for the first time [4]. ...
Wood species identification plays a crucial role in various industries, from ensuring the legality of timber products to advancing ecological conservation efforts. This paper introduces WoodYOLO, a novel object detection algorithm specifically designed for microscopic wood fiber analysis. Our approach adapts the YOLO architecture to address the challenges posed by large, high-resolution microscopy images and the need for high recall in localization of the cell type of interest (vessel elements). Our results show that WoodYOLO significantly outperforms state-of-the-art models, achieving performance gains of 12.9% and 6.5% in F2 score over YOLOv10 and YOLOv7, respectively. This improvement in automated wood cell type localization capabilities contributes to enhancing regulatory compliance, supporting sustainable forestry practices, and promoting biodiversity conservation efforts globally.
... This study is part of an extensive project that aims the traceability and authenticity of Amazonian wood based on its elemental profile. Such approach can allow the accurate identification of wood samples, once provided a robust and comprehensive database (Schmitz et al., 2020). Here, neutron activation analysis (NAA), a primary method of measurement (Greenberg et al., 2011), was used to evaluate the elemental profile and its radial distribution in three different Ipê species with high occurrence in the Amazon Rainforest: Handroanthus serratifolius (yellow Ipê), Handroanthus impetiginosus (purple Ipê), and Handroanthus leucophloeus (yellow Ipê). ...
... Addressing these challenges, dendro-provenancing has emerged as a critical tool, enhancing our knowledge of past wood harvesting and mobility, and aiding in the tracking of illegal timber logging and exports. To identify geographic provenance and wood species, various methods with unique strengths, such as varying resolution levels, and limitations, including high costs and time consumption, are often combined to enhance accuracy and comprehensiveness (Beeckman et al., 2020). Dendrochronology, the primary method in historical wood provenance studies, often overlooks multiple variables affecting tree-ring patterns (Visser, 2021). ...
... ForeST© as described typically uses Mass Mountaineer software as a shell to develop and access standard reference data-styled libraries housed within the National Institute of Standards and Technology (NIST) MS Search Program [24]. Notably, the Forest© libraries are developed by FWS and partners in-house from the reference wood samples and are not controlled or curated by NIST. ...
The mass spectral database of tree species built by US Fish and Wildlife Service has thousands of entries and has been a valuable resource to combat illegal logging and international trade. The database was and continues to be constructed using a particular ambient ionization time-of-flight mass spectrometry (TOF-MS) platform in the agency branch in Ashland, OR, with which queries of unknown wood samples are investigated exclusively. Laboratories that operate different MS instruments also have an interest in using the database if they can produce valid matches to known samples compatible with the database. Four species were selected for inter-laboratory comparison using Orbitrap MS instruments and the equivalent TOF-MS platform with direct analysis in real time ionization of institution-sourced wood samples. Identities of the known samples were confirmed by examination of their microscopic wood anatomy. Orbitrap analysis was able to identify each species as confidently as the TOF instruments, often with less variation in spectra but not necessarily greater mass accuracy or better-matched signal abundance to the control database. The Orbitrap program also had to be doubled to two scanned mass ranges appended for greater peak intensity, before spectra could be correctly matched to the database, but the program was successful.
... In this context, the accurate verification of wood species and their origin has become increasingly crucial (Van Brusselen et al. 2023). There are currently several methods available for the taxonomic and origin identification of wood in the fields of wood anatomy, genetics, stable isotopes, mass spectrometry and optical spectroscopy (Schmitz et al. 2020). Among the spectroscopic methods, near-infrared (NIR) spectroscopy has been most extensively tested as a non-destructive technique in recent decades (Wang et al., 2022Schimleck et al. 2023. ...
The recent publication of the European Regulation on deforestation, linked to the import and export from the European Union (EU) of certain commodities and products associated with deforestation and forest degradation, controls sustainable and legal sourcing of wood and wood-based products in EU. In this context, the accurate verification of wood species and their origin has become increasingly crucial. In this work, a multispectral camera was adopted to retrieve high resolution remotely sensed imagery of different wood samples exploring the spectrum between 440 and 860 nm. Eighteen wood species spectra were investigated. Starting from these spectra, linear discriminant analysis (LDA) proved that the band at 665 nm is the first discriminative feature, followed by 490 nm and 560 nm, respectively. Bands at 783 nm or higher wavelengths, i.e. the NIR region, discriminate selected species poorly. Using the first 4 linear discriminants, a classification of wood species was performed using the minimum Mahalanobis distance algorithm. The majority of species showed class accuracies between 0.7 and 0.9. However, some species showed poor performances. Cluster analysis involving all available spectra proved that the higher classification errors occurred between species of the same spectral cluster. This work shows the potentialities of adopting cheap and rapid screening tool (cameras) for separating selected wood species opening new scenarios to support industrial and commercial control processes.
The highly valuable timber species Dalbergia cochinchinensis is severely threatened due to habitat loss and illegal logging throughout its distribution in mainland Southeast Asia and is listed on CITES Appendix II. This study proposes a strategy for conservation and sustainable management of the species based on assessment of genetic structure within and among natural populations. We developed SNP markers from RAD sequencing and used these in combination with SSR genotypes from a previous study to assess the genetic diversity in 26 populations of D. cochinchinensis across its entire range in Laos, Thailand, Cambodia and Vietnam. The species is able of clonal reproduction and we found that trees closer than 45 meters from each other can be clones. Genetic diversity and clustering analysis showed a clear division of populations into five geographical groups with differing levels of diversity. Assignment tests correctly identified the region of origin for approximately 90% of the samples, which demonstrates that despite a low number of successfully identified SNPs, the SSR + SNP marker panel has the potential for tracking the geographic origin of D. cochinchinensis timber for use in CITES regulation and enforcement. We propose the five identified groups to be considered as Management Units and that conservation and breeding programs should be based on a network of in situ and ex situ conservation stands representing the genetic variation among and within these units. We recommend that conservation efforts are directed towards community owned and managed lands, as this has proven an effective strategy locally.
Using chemical fingerprints for timber species identification is a relatively new, but promising technique. However, little is known about the effect of pre-processing spectral data parameter settings on the timber species classification accuracy. Therefore, this study presents an extensive and automated analysis method using the random forest machine learning algorithm on a set of highly valuable timber species from the Meliaceae family. Metabolome profiles were collected using direct analysis in real-time (DART™) ionisation coupled with time-of-flight mass spectrometry (TOFMS) analysis of heartwood specimens for 175 individuals (representing 10 species). In order to analyse variability in classification accuracy, 110 sets of data pre-processing parameter combinations consisting of mass tolerance for binning and relative abundance cut-off thresholds were tested. Furthermore, for each set of parameters (designated “binning/threshold setting”), a random search for one hyperparameter of interest was performed, i.e. the number of variables (in this case ions) drawn randomly for each random forest analysis. The best classification accuracy (82.2%) was achieved with 47 variables and a binning and threshold combination of 40 mDa and 4%, respectively. Entandrophragma angolense is mostly confused with Entandrophragma candollei and Khaya anthotheca, and several Swietenia species are confused with each other due to the high similarity of their chemical fingerprints. Entandrophragma cylindricum, Entandrophragma utile, Khaya ivorensis, Lovoa trichilioides and Swietenia macrophylla are easy to discriminate and show less misclassifications. The choice of parameter settings, whether it is in the data pre-processing (binning and threshold) or classification algorithm (hyperparameters), results in variability in classification accuracy. Therefore, a preliminary parameter screening is proposed before constructing the final model when using the random forest algorithm for classification. Overall, DART-TOFMS in combination with random forest is a powerful tool for species identification.
• We investigate chloroplast DNA variation in a hyperdiverse community of tropical rainforest trees in French Guiana, focusing on patterns of intraspecific and interspecific variation. We test whether a species genetic diversity is higher when it has congeners in the community with which it can exchange genes and if shared haplotypes are more frequent in genetically diverse species, as expected in the presence of introgression.
• We sampled a total of 1,681 individual trees from 472 species corresponding to 198 genera and sequenced them at a noncoding chloroplast DNA fragment.
• Polymorphism was more frequent in species that have congeneric species in the study site than in those without congeners (30% vs. 12%). Moreover, more chloroplast haplotypes were shared with congeners in polymorphic species than in monomorphic ones (44% vs. 28%).
• Despite large heterogeneities caused by genus‐specific behaviors in patterns of hybridization, these results suggest that the higher polymorphism in the presence of congeners is caused by local introgression rather than by incomplete lineage sorting. Our findings suggest that introgression has the potential to drive intraspecific genetic diversity in species‐rich tropical forests.
We developed nuclear and chloroplastic single nucleotide polymorphism (SNP) and INDEL (insertion/deletion) markers using restriction associated DNA sequencing (RADSeq) and low coverage MiSeq genome sequencing to set up a genetic tracking method of the geographical origin of Hymenaea sp. From two initial sets of 358 and 32 loci used to genotype at least 94 individuals, a final set of 75 nSNPs, 50 cpSNPs and 6 INDELs identifying significant population structure was developed.
There are nearly 40 items that should ideally be reported when an NIR (near infrared) spectroscopy project is completed, either as a report or as a scientific paper. However, in our reading of the extensive literature, many of the papers presented or published report no more than 6–10 of these. The purpose of this tutorial is to indicate all of the items and the reasons for reporting them. Most of the items that need to be reported are important for anyone who seeks to duplicate the type of application and methods reported in a peer-reviewed journal article for their own work. Practically, all of the items are significant to any worker if the eventual objective of their work is to extend it to the level of industrial application. The tutorial will summarize these items, and give some explanation for their inclusion. The tutorial should be useful to potential authors, as well as to reviewers.
Confronted with growing competition, wood industry manufacturers are increasingly looking to optimize their processing processes and to control the quality of their finished products. Similarly, research and development teams in genetics and forest genetic improvement need new powerful tools enabling the evaluation of a large number of samples at a low cost and quickly. In this context, the development of non-destructive tools for measuring wood material performances (in all its forms: massive, de structured or reconstructed) is essential. Since the early 1990s, numerous research studies have explored the usefulness of using Near Infrared Spectroscopy (NIRS) to estimate the properties of wood material.This chapter, divided into two parts, aims to present a state of the art on the use of NIRS methodology in the wood domain. The first part describes technology and principles of its operation as well as its various fields of application for macromolecules, some physical and mechanical properties. The second part takes stock of the latest knowledge gained to date on the use of NIRS in the cooperage sector and takes example of an original industrial process for measuring the quality of oak wood directly on the production line.
Dipteryx timber has been heavily exploited in South America since 2000's due to the increasing international demand for hardwood. Developing tools for the genetic identification of Dipteryx species and their geographical origin can help to promote legal trading of timber. A collection of 800 individual trees, belonging to six different Dipteryx species, was genotyped based on 171 molecular markers. After the exclusion of markers out of Hardy-Weinberg equilibrium or with no polymorphism or low amplification, 83 nuclear, 29 chloroplast, 13 mitochondrial SNPs, and two chloroplast and five mitochondrial INDELS remained. Six genetic groups were identified using Bayesian Structure analyses of the nuclear SNPs, which corresponded to the different Dipteryx species collected in the field. Seventeen highly informative markers were identified as suitable for species identification and obtained self-assignment success rates to species level of 78-96%. An additional set of 15 molecular markers was selected to determine the different genetic clusters found in D. odorata and D. ferrea, obtaining self-assignment success rates of 91-100%. The success to assign samples to the correct country of origin using all or only the informative markers improved when using the nearest neighbour approach (69-92%) compared to the Bayesian approach (33-80%). While nuclear and chloroplast SNPs were more suitable for differentiating the different Dipteryx species, mitochondrial SNPs were ideal for determining the genetic clusters of D. odorata and D. ferrea. These 32 selected SNPs will be invaluable genetic tools for the accurate identification of species and country of origin of Dipteryx timber.
We developed nuclear and plastid single nucleotide polymorphism (SNP) and insertion/deletion (INDEL) markers for Dipteryx species using a combination of restriction associated DNA sequencing (RADSeq) and low coverage MiSeq genome sequencing. Of the total 315 loci genotyped using a MassARRAY platform, 292 loci were variable and polymorphic among the 73 sampled individuals from French Guiana, Brasil, Peru, and Bolivia. A final set of 56 nuclear SNPs, 26 chloroplast SNPs, 2 chloroplast INDELs, and 32 mitochondrial SNPs identifying significant population structure was developed. This set of loci will be useful for studies on population genetics of Dipteryx species in Amazonia.